Ship-YOLOv8:一种轻量级高分辨遥感图像船舶细粒度检测算法

针对高分辨率影像的船舶细粒度目标检测分类任务中类内差异大、类间相似性高、物体和场景的尺度变化范围大、特征提取困难、样本小等特点,提出了一种基于YOLOv8为基础的改进算法。首先,在骨干网络中引入SimAM注意力机制,使得模型在复杂背景中更加聚焦船舶对象;其次,在颈部引入SPD-Conv模块,改善复杂背景下船舶尺度变化大和小目标检测的问题;最后针对细粒度船舶目标检测的特点,替换Mish激活函数和Focal-Loss损失函数,加快模型收敛,提高模型精度。经对比实验可知,改进的算法在保证检测速度和模型参数量的同时,在FAIR1M_Ship数据集取得了94.49%的检测精度,与目前流行的目标检测算法相比,在检测精度上有一定的提升。

Unmanned Ship Identification Based on Improved YOLOv8s Algorithm

Aiming at defects such as low contrast in infrared ship images,uneven distribution of ship size,and lack of texture details,which will lead to unmanned ship leakage misdetection and slow detection,this paper proposes an infrared ship detection model based on the improved YOLOv8 algorithm(R_YOLO).The algorithm incorporates the Efficient Multi-Scale Attention mechanism(EMA),the efficient Reparameterized Generalized-feature extraction module(CSPStage),the small target detection header,the Repulsion Loss function,and the context aggregation block(CABlock),which are designed to improve the model’s ability to detect targets at multiple scales and the speed of model inference.The algorithm is validated in detail on two vessel datasets.The comprehensive experimental results demonstrate that,in the infrared dataset,the YOLOv8s algorithm exhibits improvements in various performance metrics.Specifically,compared to the baseline algorithm,there is a 3.1%increase in mean average precision at a threshold of 0.5(mAP(0.5)),a 5.4%increase in recall rate,and a 2.2%increase in mAP(0.5:0.95).Simultaneously,while less than 5 times parameters,the mAP(0.5)and frames per second(FPS)exhibit an increase of 1.7%and more than 3 times,respectively,compared to the CAA_YOLO algorithm.Finally,the evaluation indexes on the visible light data set have shown an average improvement of 4.5%.

Efficient Ship:A Hybrid Deep Learning Framework for Ship Detection in the River

Optical image-based ship detection can ensure the safety of ships and promote the orderly management of ships in offshore waters.Current deep learning researches on optical image-based ship detection mainly focus on improving one-stage detectors for real-time ship detection but sacrifices the accuracy of detection.To solve this problem,we present a hybrid ship detection framework which is named EfficientShip in this paper.The core parts of the EfficientShip are DLA-backboned object location(DBOL)and CascadeRCNN-guided object classification(CROC).The DBOL is responsible for finding potential ship objects,and the CROC is used to categorize the potential ship objects.We also design a pixel-spatial-level data augmentation(PSDA)to reduce the risk of detection model overfitting.We compare the proposed EfficientShip with state-of-the-art(SOTA)literature on a ship detection dataset called Seaships.Experiments show our ship detection framework achieves a result of 99.63%(mAP)at 45 fps,which is much better than 8 SOTA approaches on detection accuracy and can also meet the requirements of real-time application scenarios.

Fine-Grained Ship Recognition Based on Visible and Near-Infrared Multimodal Remote Sensing Images: Dataset,Methodology and Evaluation

Fine-grained recognition of ships based on remote sensing images is crucial to safeguarding maritime rights and interests and maintaining national security.Currently,with the emergence of massive high-resolution multi-modality images,the use of multi-modality images for fine-grained recognition has become a promising technology.Fine-grained recognition of multi-modality images imposes higher requirements on the dataset samples.The key to the problem is how to extract and fuse the complementary features of multi-modality images to obtain more discriminative fusion features.The attention mechanism helps the model to pinpoint the key information in the image,resulting in a significant improvement in the model’s performance.In this paper,a dataset for fine-grained recognition of ships based on visible and near-infrared multi-modality remote sensing images has been proposed first,named Dataset for Multimodal Fine-grained Recognition of Ships(DMFGRS).It includes 1,635 pairs of visible and near-infrared remote sensing images divided into 20 categories,collated from digital orthophotos model provided by commercial remote sensing satellites.DMFGRS provides two types of annotation format files,as well as segmentation mask images corresponding to the ship targets.Then,a Multimodal Information Cross-Enhancement Network(MICE-Net)fusing features of visible and near-infrared remote sensing images,has been proposed.In the network,a dual-branch feature extraction and fusion module has been designed to obtain more expressive features.The Feature Cross Enhancement Module(FCEM)achieves the fusion enhancement of the two modal features by making the channel attention and spatial attention work cross-functionally on the feature map.A benchmark is established by evaluating state-of-the-art object recognition algorithms on DMFGRS.MICE-Net conducted experiments on DMFGRS,and the precision,recall,mAP0.5 and mAP0.5:0.95 reached 87%,77.1%,83.8%and 63.9%,respectively.Extensive experiments demonstrate that the proposed MICE-Net has more excellent performance on DMFGRS.Built on lightweight network YOLO,the model has excellent generalizability,and thus has good potential for application in real-life scenarios.

SAR-LtYOLOv8:A Lightweight YOLOv8 Model for Small Object Detection in SAR Ship Images

The high coverage and all-weather capabilities of Synthetic Aperture Radar(SAR)image ship detection make it a widely accepted method for maritime ship positioning and identification.However,SAR ship detection faces challenges such as indistinct ship contours,low resolution,multi-scale features,noise,and complex background interference.This paper proposes a lightweight YOLOv8 model for small object detection in SAR ship images,incorporating key structures to enhance performance.The YOLOv8 backbone is replaced by the Slim Backbone(SB),and the Delete Medium-sized Detection Head(DMDH)structure is eliminated to concentrate on shallow features.Dynamically adjusting the convolution kernel weights of the Omni-Dimensional Dynamic Convolution(ODConv)module can result in a reduction in computation and enhanced accuracy.Adjusting the model’s receptive field is done by the Large Selective Kernel Network(LSKNet)module,which captures shallow features.Additionally,a Multi-scale Spatial-Channel Attention(MSCA)module addresses multi-scale ship feature differences,enhancing feature fusion and local region focus.Experimental results on the HRSID and SSDD datasets demonstrate the model’s effectiveness,with a 67.8%reduction in parameters,a 3.4%improvement in AP(average precision)@0.5,and a 5.4%improvement in AP@0.5:0.95 on the HRSID dataset,and a 0.5%improvement in AP@0.5 and 1.7%in AP@0.5:0.95 on the SSDD dataset,surpassing other state-of-the-art methods.

A Time-Domain Numerical Simulation for Free Motion Responses of Two Ships Advancing in Head Waves

The constant panel method within the framework of potential flow theory in the time domain is developed for solving the hydrodynamic interactions between two parallel ships with forward speed.When solving problems within a time domain framework,the free water surface needs to simultaneously satisfy both the kinematic and dynamic boundary conditions of the free water surface.This provides conditions for adding artificial damping layers.Using the Runge−Kutta method to solve equations related to time.An upwind differential scheme is used in the present method to deal with the convection terms on the free surface to prevent waves upstream.Through the comparison with the available experimental data and other numerical methods,the present method is proved to have good mesh convergence,and satisfactory results can be obtained.The constant panel method is applied to calculate the hydrodynamic interaction responses of two parallel ships advancing in head waves.Numerical simulations are conducted on the effects of forward speed,different longitudinal and lateral distances on the motion response of two modified Wigley ships in head waves.Then further investigations are conducted on the effects of different ship types on the motion response.

Structural Characteristics and Evolution of a Weighted Sino-US Container Shipping Network

This study selected the Sino-US route data from the top 30 global container liner companies between December 1,2019,and December 29,2019,as the data source utilizing the complex network research methodology.It constructs a Sino-US container shipping network through voyage weighting and analyzes the essential structural characteristics to explore the network’s complex structural fea-tures.The network’s evolution is examined from three perspectives,namely,time,space,and event influence,aiming to comprehens-ively explore the network’s evolution mechanism.The results revealed that:1)the weighted Sino-US container shipping network exhib-its small-world and scale-free properties.Key hub ports in the United States include NEW YORK NY,SAVANNAH GA,LOS ANGELES CA,and OAKLAND CA,whereas SHANGHAI serving as the hub port in China.The geographical distribution of these hub ports is uneven.2)Concerning the evolution of the weighted Sino-US container shipping network,from a temporal perspective,the evolution of the regional structure of the entire Sino-US region and the Inland United States is in a stage of radiative expansion and de-velopment,with a need for further enhancement in competitiveness and development speed.The evolution of the regional structure of southern China and Europe is transitioning from the stage of radiative expansion and development to an advanced equilibrium stage.The shipping development in Northern China,the Western and Eastern United States,and Asia is undergoing significant changes but faces challenges of fierce competition and imbalances.From a spatial perspective,the rationality and effectiveness of the improved weighted Barrat-Barthelemy-Vespignani(BBV)model are confirmed through theoretical derivation.The applicability of the improved evolution model is verified by simulating the evolution of the weighted Sino-US container shipping network.From an event impact per-spective,the Corona Virus Disease 2019(COVID-19)pandemic has not fundamentally affected the spatial pattern of the weighted Sino-US container shipping network but has significantly impacted the network’s connectivity.The network lacks sufficient resilience and stability in emergency situations.3)Based on the analysis of the structural characteristics and evolution of the weighted Sino-US con-tainer shipping network,recommendations for network development are proposed from three aspects:emphasizing the development of hub ports,focusing on the balanced development of the network,and optimizing the layout of Chinese ports.

Improved Scatter Search Algorithm for Multi-skilled Personnel Scheduling of Ship Block Painting

This paper focuses on the optimization method for multi-skilled painting personnel scheduling.The budget working time analysis is carried out considering the influence of operating area,difficulty of spraying area,multi-skilled workers,and worker’s efficiency,then a mathematical model is established to minimize the completion time. The constraints of task priority,paint preparation,pump management,and neighbor avoidance in the ship block painting production are considered. Based on this model,an improved scatter search(ISS)algorithm is designed,and the hybrid approximate dynamic programming(ADP)algorithm is used to improve search efficiency. In addition,the two solution combination methods of path-relinking and task sequence combination are used to enhance the search breadth and depth. The numerical experimental results show that ISS has a significant advantage in solving efficiency compared with the solver in small scale instances;Compared with the scatter search algorithm and genetic algorithm,ISS can stably improve the solution quality. Verified by the production example,ISS effectively shortens the total completion time of the production,which is suitable for scheduling problems in the actual painting production of the shipyard.

Time-Domain Higher-Order Boundary Element Method for Simulating High Forward-Speed Ship Motions in Waves

The hydrodynamic performance of a high forward-speed ship in obliquely propagating waves is numerically examined to assess both free motions and wave field in comparison with a low forward-speed ship.This numerical model is based on the time-domain potential flow theory and higher-order boundary element method,where an analytical expression is completely expanded to determine the base-unsteady coupling flow imposed on the moving condition of the ship.The ship in the numerical model may possess different advancing speeds,i.e.stationary,low speed,and high speed.The role of the water depth,wave height,wave period,and incident wave angle is analyzed by means of the accurate numerical model.It is found that the resonant motions of the high forward-speed ship are triggered by comparison with the stationary one.More specifically,a higher forward speed generates a V-shaped wave region with a larger elevation,which induces stronger resonant motions corresponding to larger wave periods.The shoaling effect is adverse to the motion of the low-speed ship,but is beneficial to the resonant motion of the high-speed ship.When waves obliquely propagate toward the ship,the V-shaped wave region would be broken due to the coupling effect between roll and pitch motions.It is also demonstrated that the maximum heave motion occurs in beam seas for stationary cases but occurs in head waves for high speeds.However,the variation of the pitch motion with period is hardly affected by wave incident angles.

Decoding RoPax Ship Capsizes and Development of an ISO Ship Safety Standard

Marine accidents often result in significant losses of human life, environmental damage, and property destruction. Additionally, ships and offshore plants are large-scale and complex systems, making safety assessments challenging. However, the advent of onboard electronic systems has made it possible to monitor and respond more effectively. These new technologies can enhance safety levels while reducing the workload on crews. In this paper, authors analyze recent accidents involving ships with high structures above the water, such as car carriers or RoPax vessels, and propose preventive safety indicators to help prevent similar accidents from recurring.

Sending The King Ship, A Tradition Connecting Two Peoples

“The sky is dark,and it is about to rain,”goes a lyric from China’s coastal Minnan(southern Fujian)region.“The king ship is leaving the bay,papa is going out to sea,and mama is sending the ship off.May it bring us wealth,food,and the gods’protection.”The 600-year-old custom is called Ong Chun,Wangchuan,Wangkang,or“Sending the King Ship.”

Ship recognition based on HRRP via multi-scale sparse preserving method

In order to extract the richer feature information of ship targets from sea clutter, and address the high dimensional data problem, a method termed as multi-scale fusion kernel sparse preserving projection(MSFKSPP) based on the maximum margin criterion(MMC) is proposed for recognizing the class of ship targets utilizing the high-resolution range profile(HRRP). Multi-scale fusion is introduced to capture the local and detailed information in small-scale features, and the global and contour information in large-scale features, offering help to extract the edge information from sea clutter and further improving the target recognition accuracy. The proposed method can maximally preserve the multi-scale fusion sparse of data and maximize the class separability in the reduced dimensionality by reproducing kernel Hilbert space. Experimental results on the measured radar data show that the proposed method can effectively extract the features of ship target from sea clutter, further reduce the feature dimensionality, and improve target recognition performance.

Novel method for extraction of ship target with overlaps in SAR image via EM algorithm

The quality of synthetic aperture radar(SAR)image degrades in the case of multiple imaging projection planes(IPPs)and multiple overlapping ship targets,and then the performance of target classification and recognition can be influenced.For addressing this issue,a method for extracting ship targets with overlaps via the expectation maximization(EM)algorithm is pro-posed.First,the scatterers of ship targets are obtained via the target detection technique.Then,the EM algorithm is applied to extract the scatterers of a single ship target with a single IPP.Afterwards,a novel image amplitude estimation approach is pro-posed,with which the radar image of a single target with a sin-gle IPP can be generated.The proposed method can accom-plish IPP selection and targets separation in the image domain,which can improve the image quality and reserve the target information most possibly.Results of simulated and real mea-sured data demonstrate the effectiveness of the proposed method.

欧盟AUTOSHIP项目

欧洲水域自主航运倡议项目(Autonomous Shipping Initiative for European Waters,AUTOSHIP项目)由意大利Ciaotech S.r.l.公司牵头,联合康士伯等其他欧洲国家合作伙伴共同完成。该项目通过在不同环境下运营的两艘不同类型船舶上安装和测试自主航行设施,加速新一代自主航行船舶发展,并为欧盟实现船舶自主航行制定商业化路线图。

Corporate Social Responsibility and Shipping Supply Chain Risks

This study aims to investigate whether Corporate Social Responsibility(CSR)activities reduce supply chain disruptions by examining the impact of the Suez Canal obstruction on the Ever Given container ship in March 2021.This study conclude that the more responsible companies have higher returns and are less affected by this event than the less responsible companies;the less responsible companies have lower returns.The companies with better CSR have a lower impact on their supply chains when faced with disruptions in the supply chain.

伊马替尼对K562细胞内SHIP基因表达的影响及促凋亡作用

目的:观察甲磺酸伊马替尼干预K562细胞后SHIP、caspase-1、caspase-3、caspase-9及bcl-2基因表达的变化,初步探讨伊马替尼促凋亡的作用途径。方法:将不同浓度甲磺酸伊马替尼与K562细胞在体外共培养,于不同时段留取标本,采用实时定量PCR方法检测SHIP基因表达水平的变化,并用半定量逆转录PCR方法检测抗凋亡基因bcl-2及促凋亡基因caspase-1、caspase-3、caspase-9表达水平的变化,用MTT法观察伊替尼对细胞增殖的抑制作用,用膜联蛋白Ⅴ/碘化丙锭(AnnexinⅤ/PI)双标记法分析细胞凋亡。结果:甲磺酸伊马替尼可使K562细胞内SHIP基因表达水平升高,且与剂量和作用时间有关;caspase-9表达水平亦升高并与SHIP基因表达水平有直线相关关系;而caspase-1、caspase-3和bcl-2表达水平无显著变化;伊马替尼可使细胞增殖率降低、凋亡率增加,并可见到明显的形态学变化。结论:甲磺酸伊马替尼可使K562细胞内SHIP及caspase-9基因表达水平升高且可促进细胞凋亡,其促凋亡作用机制可能与上调SHIP和caspase-9基因表达有关。

急性白血病细胞SHIP基因的突变分析(英文)

SHIP (SH2domaincontaininginositol5′ phosphatase)基因主要在造血细胞表达 ,并在造血细胞的发生发育中发挥关键的负调节作用。本研究旨在评价SHIP基因突变在白血病发病中的作用。利用RT PCR、SSCP及DNA序列分析技术检测了 32例急性髓细胞白血病、9例急性淋巴细胞白血病及正常对照骨髓或外周血标本中SHIP基因表达及突变情况。RT PCR显示所有标本中都有SHIP基因表达 ,2 2 % (7/32 )AML和 12 % (1/9)ALL标本中存在SHIP基因的突变 ,其中 1例AML患者发病时标本同时存在 2个错义突变 ,而完全缓解 (CR)后消失 ,而且其发病时的白血病细胞在体外随着IL 3的刺激其Akt的磷酸化明显增加。结论 :本研究首次发现急性白血病细胞中SHIP基因突变 ,提示SHIP基因的突变可能与白血病发病有关 ;在造血细胞中 ,它很可能做为一个抑癌基因通过负性调节PI3K/Akt信号通路发挥作用。

硼替佐米对K562细胞增殖、凋亡及SHIP基因表达的影响

本研究旨在探讨蛋白酶体抑制剂硼替佐米(bortezomib)对K562细胞的增殖、凋亡及SHIP基因表达的影响。将不同浓度的硼替佐米作用于K562细胞,采用MTT法测定细胞增殖活性,用流式细胞术检测细胞凋亡,RT-PCR方法检测SHIP mRNA表达。结果表明,硼替佐米10、20、50和100 nmol/L作用于K562细胞24 h,细胞增殖抑制率分别为(5.76±1.47)%、(10.55±1.59)%、(17.14±2.05)%和(27.69±3.57)%,空白对照组为(1.30±0.10)%;20nmol/L硼替佐米作用于K562细胞24、48、72 h,细胞增殖抑制率分别为(10.55±1.59)%、(16.33±2.53)%、(19.78±1.56)%,24 h组与48 h组比较,差异具有统计学意义(P<0.05),10、20、50、100 nmol/L硼替佐米作用于K562细胞24h,Annexin V-FITC/PI双标法显示其凋亡率分别为(12.7±0.6)%、(26.9±0.9)%、(32.6±1.2)%、(72.5±1.5)%,均高于对照组(1.0±0.5)%(P<0.05)。RT-PCR法检测结果显示应用硼替佐米作用后SHIP mRNA表达上调明显,与空白对照组比较差异有统计学意义。结论:硼替佐米呈时间、浓度依赖性抑制K562细胞增殖,并能通过上调SHIP基因的表达诱导细胞凋亡。

外源性SHIP基因对K562细胞周期及其相关蛋白表达的影响

目的:探讨SHIP基因对人白血病细胞系K562细胞周期的调控作用。方法:用携带野生型SHIP基因及绿色荧光蛋白(green fluorescent protein,GFP)基因的慢病毒及空载体慢病毒转染人白血病K562细胞。FCM检测转染效率、细胞凋亡率及细胞周期变化,实时荧光定量PCR(real-time fluorescent quantitative PCR,RFQ-PCR)检测SHIPmRNA水平的变化,Western印迹法检测SHIP、cyclinD1、p21WAF1/CIPI、p27KIP1蛋白表达水平的变化。结果:与转染空载体组和未转染组相比,转染野生型SHIP基因的K562细胞增殖减慢,凋亡率明显上升(P<0.05);细胞周期显示,G0/G1期延长,G1期前出现亚二倍体的凋亡峰,S期和G2/M期比例降低;cyclin D1表达降低,p21WAF1/CIPI和p27KIP1表达增加。结论:转染野生型SHIP基因可使细胞周期阻滞在G0/G1期,抑制白血病细胞增殖,促进白血病细胞凋亡。

抗小鼠SHP-1、SHP-2和SHIP三种蛋白酪氨酸磷酸酶单克隆抗体的制备及鉴定

为了制备抗小鼠蛋白酪氨酸磷酸酶的单克隆抗体（mAb），分别以SHP-1、SHP-2和SHIP重组蛋白为抗原免疫BALB／c小鼠，通过B淋巴细胞杂交瘤技术制备抗相应磷酸酶的mAb。用Western blot检测mAb对重组蛋白和细胞中天然磷酸酶的反应性。共获得12株可稳定分泌抗磷酸酶mAb的杂交瘤细胞株。其中6株可分泌抗SHP—1 mAb（LX～SHPl．1～LX—SHP1．6），3株可分泌抗SHP-2 mAb（LX—SHP2．1～LX—SHP2．3），3株分泌抗SHIP mAb（LX—SHIP1～LX—SHIP3）。LX-SHP1．2～LX—SHP1．6，LX-SHP2．1和LXSHP2．3，以及LX—SHIP2和LX—SHIP3可应用于相应重组蛋白的Western blot检测。LX-SHP1．5，LX—SHP2，3，以及LX—SHIP2在EL-4细胞及原代T细胞相应天然磷酸酶分子的Western blot检测中有较好的实验效果。